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Comparative transcriptome analysis of two Ipomoea aquatica Forsk. cultivars targeted to explore possible mechanism of genotype dependent accumulation of cadmium Ying-Ying Huang, Chuang Shen, Jing-Xin Chen, Chun-Tao He, Qian Zhou, Xiao Tan, Jiangang Yuan, and Zhongyi Yang J. Agric. Food Chem., Just Accepted Manuscript • DOI: 10.1021/acs.jafc.6b01267 • Publication Date (Web): 06 Jun 2016 Downloaded from http://pubs.acs.org on June 8, 2016
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Journal of Agricultural and Food Chemistry
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Comparative transcriptome analysis of two Ipomoea aquatica Forsk. cultivars
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targeted to explore possible mechanism of genotype dependent accumulation of
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cadmium
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Ying-Ying Huang, Chuang Shen, Jing-Xin Chen, Chun-Tao He, Qian Zhou, Xiao Tan,
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Jian-Gang Yuan and Zhong-Yi Yang*
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State Key Laboratory for Biocontrol, School of Life Sciences, Sun Yat-Sen University,
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Xingang Xi Road 135, Guangzhou, 510275, China
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*
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Mail address: Xingang Xi Road 135, Guangzhou, 510275, China.
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Email:
[email protected] 14
Tel: +86 2084113220
Corresponding Author
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ABSTRACT
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A low-shoot-Cd (QLQ) and a high-shoot-Cd cultivar (T308) of water spinach
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(Ipomoea aquatica Forsk.) were used to investigate molecular mechanism of the
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genotype difference in cadmium (Cd) accumulation. RNA-Seq under 9 h and 72 h
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cadmium exposures (5 mg L-1) were undertaken to explore Cd induced genotype
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differences in molecular processes. In total, 253,747,540 clean reads were assembled
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into 57,524 unigenes. Among them, 6,136 and 10,064 unigenes were differentially
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expressed in QLQ and T308, respectively. Cell wall biosynthesis genes such as GAUT
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and laccase and three Cd efflux genes (Nramp5, MATE9 and YSL7) had higher
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expression levels in QLQ, while the genes in sulfur and glutathione metabolism
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pathway e.g. sulfate transporter and cysteine synthase showed higher expression
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levels in T308. These findings would be useful for further understanding of the
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mechanisms related to genotype-dependent Cd accumulation and developing the
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molecular assisted screening and breeding of low-shoot-Cd cultivars for water
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spinach.
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Low-shoot-Cd
accumulation,
Water
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KEYWORDS:
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aquatica Forsk.), Transcriptome, DEGs, Molecular mechanisms
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spinach
(Ipomoea
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INTRODUCTION
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Cadmium (Cd) is a non-essential element with high toxicity and can be
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accumulated in the human body over time from the digestion of food containing Cd,
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being a threat to human health with excessive intake 1, 2. Cd contamination has been a
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worldwide environmental problem 3. Therefore, take efficient technologies to reduce
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Cd content in crops is crucially important. Wide variations among cultivars in the
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concentration of Cd have been reported in many species, including rice (Oryza sativa)
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4
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spinach (Ipomoea aquatic Forsk.) 8. It has been indicated that low-Cd cultivars can be
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used to reduce the movement of Cd into the human diet 1.
, asparagus bean (Dolichos sinensis) 5, hot pepper (Capsicum annuum) 6, 7 and water
Water spinach is an important leafy vegetable in southern China, it can
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8, 9
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accumulate Cd easily when growing in Cd-contaminated soils
. A high-shoot-Cd
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cultivar (T308) and a low-shoot-Cd cultivar (QLQ) were identified in our previous
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studies
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the differences between shoot concentrations of the two cultivars were 3.1~3.4 fold 9.
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A reciprocal grafting experiment of QLQ and T308 showed that the plants of T308
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scion with QLQ rootstock accumulated less Cd than the shoot of non-grafted T308
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and the plants of QLQ scion with T308 rootstock accumulated higher Cd than the
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shoots of non-grafted QLQ. These observations indicated that the genotype-dependent
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Cd accumulation of water spinach largely depends on bio-processes occurring in roots
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and T308) had been observed by suppression subtractive hybridization (SSH) in our
8, 10
. When growing in Cd contaminated soil (0.593 mg kg-1dry weight, DW),
. Cd-induced gene expression differences of the two water spinach cultivars (QLQ
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previous study
. Although there are some studies focus on the molecular
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mechanisms of Cd hyperaccumulation in several species
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mechanisms of cultivar dependent difference in Cd accumulation of crops are poorly
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understood
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mechanisms of low-shoot-Cd accumulation of water spinach at transcriptional level.
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For water spinach, which has no reference genome , de novo assembly using
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high-throughput deep sequencing technology is an effective approach for
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transcriptome analysis. RNA-Seq has been successfully used in studies of Cd stressed
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Noccaea caerulescens and Sedum alfredii which has also no reference genome 16, 17.
13, 14
, the molecular
1, 15
. The objective of this study is to uncover the possible molecular
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Accordingly, RNA-Seq is employed to explore the differences in root
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transcriptional responses to Cd stress between the two cultivars after short- (9 h) and
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long-term (72 h) Cd treatment. To our knowledge, this is the first attempt to use
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RNA-Seq to detect Cd-induced transcriptional differences between two water spinach
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cultivars with different Cd accumulation abilities. It is expected that the results will
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help to clarify molecular mechanisms that are responsible for low-shoot-Cd
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accumulation in water spinach and will be useful to build up breeding methodology of
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low Cd accumulation cultivars based on molecular assistant breeding techniques.
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METHODS AND MATERIALS
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Plant Materials and Treatments
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Two water spinach cultivars, QLQ (low-shoot-Cd cultivar) and T308
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(high-shoot-Cd cultivar) were used in this study. The two cultivars were selected from
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30 cultivars in our previous study, and the differences between shoot Cd
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concentrations of the two cultivars were 3.1~3.4 fold when grew in Cd contaminated
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soil (0.593 mg kg-1 dry weight, DW) 9. When grew in Hoagland solution containing 6
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mg L-1 CdCl2 for 24 h, the differences between shoot Cd concentrations was 1.6 fold
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12
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. Seeds of the cultivars were surface disinfected with 1‰ carbendazim (m/v)
for
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0.5 h, then thoroughly washed with deionized water, and sown into pots filled with
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sand (3 plants per pot) and then were irrigated with a half strength Hoagland nutrient
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solution for 4 weeks. The plants were cultured at constant temperature condition (25±
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1°C) with a photoperiod of 14 h (12000 lx). Three Cd exposure lengths were then
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carried out as treatment by irrigating with the half strength Hoagland solution
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containing 5 mg L-1 CdCl2 for 0 h, 9 h and 72 h, respectively. The three treatment
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groups were denoted as E0, E9 and E72, respectively, and each treatment repeated 3
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times.
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The shoots and roots of the three plants for each treatment were harvested
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separately and then washed with deionized water. Thereafter one plant is randomly
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selected from each pot for further study.
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Determination of Cd Concentration
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The roots were washed thorough with tap water and soaked in 25 mM CaCl2
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twice (5 min each time) to remove heavy metal ions from the root surface. All
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samples were thoroughly washed with deionized water, dried at 105°C for 30 min,
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and then dried at 70°C to constant weight. The dried samples were digested (HNO3:
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H2O2, 5:1) and then analyzed by atomic absorption spectroscopy (Hitachi Z-5300,
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Japan). A certified reference material (CRM) of plant (GBW-07603, provided by the
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National Research Center for CRM, China) with a Cd concentration of 0.38 mg kg-1
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was used to control the precision of the analytical procedures. Data statistical analyses
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including independent samples t-test and one-way ANOVA with the least significant
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difference (LSD) test were performed using excel 2013 and SPSS 18.0.
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RNA Extraction
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Total RNA were extracted separately from the root samples of the three plants as
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replicates for each treatment with the aid of the RNA Easyspin Isolation System
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(Aidlab, China) according to the manufacturer’s instruction, and the genomic DNA
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residues were removed during RNA extraction. RNA concentration and quality were
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tested in an Agilent 2100 Bioanalyzer (Agilent, USA). RNA quality was also
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confirmed by RNase free agarose gel electrophoresis. Equal amounts of total RNA
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extracted from the three replicate plants of each treatment were pooled to construct
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the cDNA library, so so 6 cDNA libraries (2 cultivars × 3 treatments) were
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constructed in the present study. Pooling is a cost-effective strategy to identify gene
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expression profiles and has been well-justified based on statistical and practical
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considerations 18.
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cDNA Library Construction and Sequencing
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Poly (A) mRNA was isolated by using oligo-dT beads (Qiagen, USA) and
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broken down into short fragments (200 nt) by adding fragmentation buffer.
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First-strand cDNA was generated using random hexamer-primed reverse transcription
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and second-strand cDNA was synthesized using RNase H and DNA polymerase I.
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The cDNA fragments were purified with a QIAquick PCR purification kit (Qiagen,
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USA) and resolved with EB buffer for end reparation, poly (A) addition and ligated to
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sequencing adapters. After agarose gel electrophoresis, suitable fragments (about 200
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nt) were used to construct the final cDNA library and was sequenced using Illumina
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HiSeq™ 2000 (pair-end sequencing, length 125 bp).
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De Novo Transcriptome Assembly and Annotation
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Illumina adapter sequences were cut, and low quality reads that did not meet the
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quality threshold were removed by a Perl program (version 5.18.4). Raw reads
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containing adapter, reads with more than 10% unknown nucleotides, and low quality
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reads with over 50% low Q-value (≤5) base were removed as well. The clean reads
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were de novo assembled using Trinity 2.0 19. The resulting transcripts were annotated
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with BLASTX (version 2.2.29), a tool widely used to search sequence similarities, by
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comparing against the database of NCBI non-redundant protein database (Nr,
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http://www.ncbi.nlm.nih.gov/), Cluster of Orthologous Groups of proteins database
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(COG, http://www.ncbi.nlm.nih.gov/COG/), Kyoto Encyclopedia of genes and
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genomes
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(http://www.expasy.ch/sprot), with an e-value cut off of 10-5.
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Identification of Differentially Expressed Genes
(KEGG,
http://www.genome.jp/kegg/)
and
Swiss-Prot
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Clean reads were used to map reference sequence by SOAPaligner/soap2
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(version 2.21), a tool designed for short sequence alignment. The expression levels of
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all genes were determined using the RPKM (reads per kb per million reads) method ,
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according to the formula of RPKM (A)=106C/(NL 10-3). In which, RPKM stands for
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the expression of gene A; C stands for the number of reads uniquely mapped to gene
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A; N stands for the number of reads uniquely mapped to all genes; L stands for the
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total length of gene A. For genes with more than one alternative transcript, the longest
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transcript was used to calculate the RPKM
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influence of different gene lengths and sequencing discrepancies on the gene
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expression calculation. The false discovery rate (FDR) was calculated to adjust the
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threshold of p value using the method described by Benjamini et al
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between each two samples were considered differentially expressed when the false
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discovery (FDR) ≤ 0.001 and the absolute value of log2Ratio≥ 1.
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GO and Pathway Enrichment Analyses of DEGs
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. The RPKM method can eliminate the
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. Unigenes
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To determine the main biological functions of the differentially expressed genes,
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Gene Ontology (GO, http://www.geneontology.org/) terms were assigned by using
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Blast2GO (version 2.8) to search the Nr database 22. GO classification was performed
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in WEGO (http://wego.genomics.org.cn/cgi-bin/wego/index.pl)
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categorization results were expressed as 3 independent hierarchies for molecular
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function, biological process and cellular component. The KEGG pathway annotation
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was performed using BLASTX software against the Kyoto Encyclopedia of Genes
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and Genomes (KEGG) database according to the method described by Kanehisa et al
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24
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correction, and a corrected p-value≤ 0.05 was chosen as the threshold value to
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determine significantly enriched GO terms. For KEGG enrichment analysis, the
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pathway with a FDR value≤ 0.05 was considered as an enriched pathway. Pearson
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, and the GO
. For GO enrichment analysis, all p-values were adjusted with the Bonferroni
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correlation coefficient analysis and principal component analysis (PCA) on all
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samples were performed by R package (version 3.1.3, http://www.r-project.org/) using
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the log transformed RPKM values of all genes.
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Quantitative Real-Time Reverse Transcription PCR
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The expression levels of 20 genes were determined by quantitative real-time
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reverse transcription PCR (qRT-PCR). First strand cDNA was generated by purified
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total RNA using a PrimeScriptTM RT regent kit (Takara, Japan). The water spinach
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actin (unigene0033718) was selected as a reference gene. All primers for qRT-PCR
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were shown in Table S1 (suporting information). qRT-PCR was performed on a
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LightCycler® 480 Real-Time PCR System (Roche, Germany) with SYBR GreenII
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PCR Master Mix (Takara, Japan). The qPCR cycling program was run as follows:
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95°C for 3 min, followed by 45 cycles of 95°C for 15 sec and 60°C for 1 min. Each
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qRT-PCR analysis was performed in triplicate. Results were analyzed with the
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integrated LightCycler® 480 service software. Expression levels of the tested genes
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were determined by CT values and calculated by the ∆∆Ct method.
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RESULTS
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Cd Concentration of Water Spinach
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Root dry weight in both two cultivars at E9 and E72 did not show significant
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differences compared with those at E0 (Figure S1). Shoot and root Cd concentrations
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of water spinach cultivars QLQ and T308 are shown in Figure 1. Concentrations in
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both cultivars increased with duration of Cd treatment. T308 always accumulated
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higher Cd in shoots than QLQ, but only the difference at E72 was significant
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(p0.05).
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De Novo Sequence Assembly and Functional Annotation
-1
(dry weight basis), respectively, indicating that the genotype
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RNA-Seq analyses of the two cultivars were performed on the Illumina system to
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explore the differences that may contribute to their metal-related traits at
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transcriptional level in roots. As mentioned before that there is no appropriate
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reference genome sequence available for water spinach, therefore all the 253,747,540
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clean reads were de novo assembled using Trinity to construct unique consensus
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sequence. The assembly yielded a total of 57,524 unigenes with an N50 unigene size
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of 1,627 bp, an average length of 936.74 bp, a minimum length of 201 bp and a
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maximum length of 17,439 bp. A summary of the unigenes size distribution is given
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in Figure S2. The raw reads of RNA sequencing were deposited in the Sequence Read
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Archive (SRA) database of NCBI with the accession number of SRP071620.
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Only 55.81% (32104) unigenes of all the assembled unigenes (57,524) could be
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annotated to the 4 databases (Nr, Swiss-Prot, COG and KEGG). GO analysis was
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performed to classify the function of annotated unigenes. GO analysis categorized
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16,394 unigenes belonging to cellular component, biological process and molecular
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function in which cell (8,049), metabolic process (8,734), and catalytic activity (7,981)
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was the dominant groups, respectively (Figure S3). In addition, 9,166 unigenes were
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mapped to 125 KEGG pathways. The dominant pathway with most unigenes was
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metabolic pathways, followed by biosynthesis of secondary metabolite, ribosome and
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plant hormone signal transduction (Table S2).
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The Pearson correlation between QLQ-72 h and QLQ- 0 h was lower than that
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between QLQ-9 h and QLQ-0 h, while it was reversed in T308. The correlations
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between two cultivars decreased with duration of Cd treatment (Table S3). Principal
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component analysis (PCA) showed that 68.8% of the transcriptional changes
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associated with Cd stress were explained by the first two PCA components. The first
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and second component did not cluster the samples by Cd treatment time in both two
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cultivars, but the transcriptional response to Cd stress of QLQ and T308 could be
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separated by PCA analyses. For the first principal component, assignment of QLQ-72
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h was similar to that of T308-9 h (Figure S4).
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Differential Expressed Genes (DEGs)
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Unigenes were commonly considered differentially expressed when the FDR ≤
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0.001 and the absolute value of log2Ratio ≥ 1. RNA-Seq data showed that the gene
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expression profiles of the both cultivars changed significantly after exposing to 5 mg
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L-1 CdCl2 at E9 and E72 as compared to E0. The number of DEGs between two
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cultivars increased over time, and this result was comparable with the increment of
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the differences in shoot Cd concentrations between two cultivars (Table S4). DEGs
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between QLQ and T308 at E9 and E72 obtained from Venn analysis are shown in
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Figure 2. A total of 79 up-regulated and 98 down-regulated unigenes were shared by
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QLQ and T308 at different treatment time (Table S5).
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Trend Analysis of DEGs
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To examine the expression profile of the DEGs in QLQ and T308, trend analysis
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were performed by Short Time-series Expression Miner (STEM) Software. A total of
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6,136 DEGs in QLQ were clustered into 8 profiles, and only 2 profiles recorded with
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a significance p